Objective A fundamental challenge in treating epilepsy is that changes in observed seizure
frequencies do not necessarily reflect changes in underlying seizure risk. Rather, changes in …

Background There is currently no formal method for predicting the range expected in an
individual's seizure counts. Having access to such a prediction would be of benefit for …

People with epilepsy have variable and dynamic trajectories in response to antiseizure
medications. Accurately modelling long-term treatment response will aid prognostication at …

Objective Seizure unpredictability is rated as one of the most challenging aspects of living
with epilepsy. Seizure likelihood can be influenced by a range of environmental and …

Objective Our objective was to develop a generalized linear mixed model for predicting
seizure count that is useful in the design and analysis of clinical trials. This model also may …

Accurate prediction of seizures in persons with epilepsy offers opportunities for both
precautionary measures and preemptive treatment. Previously identified predictors of …

Epilepsy is a unique neurologic condition characterized by recurrent seizures, where
causes, underlying biomarkers, triggers, and patterns differ across individuals. The …

Objective To analyze data from Seizure Tracker, a large electronic seizure diary, including
comparison of seizure characteristics among different etiologies, temporal patterns in …

Objective We conducted clinical testing of an automated Bayesian machine learning
algorithm (Epilepsy Seizure Assessment Tool [EpiSAT]) for outpatient seizure risk …

Studies suggest that self‐reported seizure diaries suffer from 50% under‐reporting on
average. It is unknown to what extent this impacts medication management. This study used …